This review focuses on the definitions, modalities, applications, and performance of various
aspects of digital twins (DTs) in the context of transmission and industrial machinery. In this …

In recent decades, exogenous pressures have contributed to habitat loss and fragmentation
of oysters, resulting in a growing interest in restoring oyster reefs. Hydrodynamics of oyster …

The chiller fault diagnosis is of great significance to maintain the normal operation of the
HVAC system and indoor comfort. Due to the difficulty in collecting the chiller's fault data, we …

Rolling bearings are crucial for ensuring the safe and stable operation of electromechanical
systems. Although deep learning has been widely used in fault diagnosis of rolling bearings …

Detecting faults in high-speed and high-power diesel engines under complex variable
operating conditions is highly challenging. Online vibration monitoring systems have been …

As one of the most critical variables in the hot rolling process, the accuracy of rolling force
prediction is directly associated with production stability and product quality. Purely data …

Due to their short duration, concealability, and random occurrence, intermittent faults have
become the most dangerous hazard in electronic circuit systems. However, existing …

The fault diagnosis of mechanical equipment can prevent potential mechanical failures,
avoid property damage and personal injury, and ensure the stable and safe operation of …

Artificial intelligence (AI)-driven fault diagnosis methods are crucial for ensuring rotating
machinery's safety and effective operation. The success of most current methods relies on …

Machinery fault diagnosis based on deep learning methods is cost-effective to guarantee
safety and reliability of mechanical systems. Due to the variability of machinery working …